Application Number: 1 U01 MH103018-01 (Formerly: 1U01AG046691-01) HUSKAMP, HAIDEN A. PHD NORMAND, SHARON-LISE TERESA PHD (Contact) Technology Diffusion Pathways DESCRIPTION: Over the past several years, there has been increasing focus on provider organizations as the locus of responsibility for the cost and quality of health care that is delivered. A number of new strategies to contain spending growth and improve quality of care encourage provider organizations to meet these goals through delivery system changes. Adoption of new medical technology is a primary driver of health care spending growth. Physicians and the organizations in which they practice have various options to adopt and use new and existing technologies. Their choices can potentially improve efficiency of care, but might not prove optimal depending on which technologies are adopted more quickly versus more slowly, and the impact of such strategies will likely vary across organizations. Using a rich collection of data for the period 2005-2015, we propose to examine the relationship between organization traits and diffusion of technology. In Aim 1 we will study the diffusion of selected new technologies, including technologies we designate to be of higher and lower value, in 4 disease categories - cancer, depression, cardiac, and hip degeneration - as a function of organization characteristics. Our statistical methods include properties of diffusion curves, and provide new approaches to characterize the path of technology adoption. These approaches enable determination of whether decisions to use new technologies are correlated among different technology types, or within and between disease conditions. In Aim 2, using quality measures promulgated by professional societies, technology characteristics, and FDA alerts, we will distinguish higher from lower value services, identify organizational factors predictive of their use, and determine if decisions to adopt higher vs. lower value services are correlated. In Aim 3, we will identify organizational characteristics, adjusting for physician and patient factors, associated with spending for new technologies and for lower vs. higher value services. Most research on technological adoption and diffusion consists of case studies of single technologies. Our study will compare rates of adoption and use across types of technologies (medications, devices, and biologics) within disease areas, across lower and higher value technologies, and across organizational forms.